scholarly journals The chaos in calibrating crop models

2020 ◽  
Author(s):  
Daniel Wallach ◽  
Taru Palosuo ◽  
Peter Thorburn ◽  
Zvi Hochman ◽  
Emmanuelle Gourdain ◽  
...  
Keyword(s):  
Experimental Data ◽  
Model Calibration ◽  
Crop Model ◽  
Process Models ◽  
Model Parameters ◽  
Model Structure ◽  
Crop Models ◽  
Estimation Of Model Parameters ◽  
Parameter Values ◽  
Made In

Calibration, that is the estimation of model parameters based on fitting the model to experimental data, is among the first steps in essentially every application of crop models and process models in other fields and has an important impact on simulated values. The goal of this study is to develop a comprehensive list of the decisions involved in calibration and to identify the range of choices made in practice, as groundwork for developing guidelines for crop model calibration starting with phenology. Three groups of decisions are identified; the criterion for choosing the parameter values, the choice of parameters to estimate and numerical aspects of parameter estimation. It is found that in practice there is a large diversity of choices for every decision, even among modeling groups using the same model structure. These findings are relevant to process models in other fields.

scholarly journals Simulating tubulin-associated unit transport in an axon: using bootstrapping for estimating confidence intervals of best-fit parameter values obtained from indirect experimental data

2017 ◽  
Vol 473 (2201) ◽  
pp. 20170045 ◽  
Author(s):  
I. A. Kuznetsov ◽  
A. V. Kuznetsov
Keyword(s):  
Experimental Data ◽  
Confidence Intervals ◽  
Surrogate Data ◽  
Model Parameters ◽  
Model Predictions ◽  
Estimate Parameter ◽  
Minimum Number ◽  
Percentile Bootstrap ◽  
Parameter Values ◽  
Best Fit

In this paper, we first develop a model of axonal transport of tubulin-associated unit (tau) protein. We determine the minimum number of parameters necessary to reproduce published experimental results, reducing the number of parameters from 18 in the full model to eight in the simplified model. We then address the following questions: Is it possible to estimate parameter values for this model using the very limited amount of published experimental data? Furthermore, is it possible to estimate confidence intervals for the determined parameters? The idea that is explored in this paper is based on using bootstrapping. Model parameters were estimated by minimizing the objective function that simulates the discrepancy between the model predictions and experimental data. Residuals were then identified by calculating the differences between the experimental data and model predictions. New, surrogate ‘experimental’ data were generated by randomly resampling residuals. By finding sets of best-fit parameters for a large number of surrogate data the histograms for the model parameters were produced. These histograms were then used to estimate confidence intervals for the model parameters, by using the percentile bootstrap. Once the model was calibrated, we applied it to analysing some features of tau transport that are not accessible to current experimental techniques.

Operational analysis of the spatial distribution and the temporal evolution of the snowpack water equivalent in southern Québec, Canada

2007 ◽  
Vol 38 (3) ◽  
pp. 211-234 ◽  
Author(s):  
R. Turcotte ◽  
L.-G. Fortin ◽  
V. Fortin ◽  
J.-P. Fortin ◽  
J.-P. Villeneuve
Keyword(s):  
Survey Data ◽  
Model Calibration ◽  
Hydrological Model ◽  
Temporal Evolution ◽  
Regional Analysis ◽  
Model Parameters ◽  
Snow Density ◽  
Operational Analysis ◽  
Grid Points ◽  
Made In

A technique for obtaining an operational regional analysis of the temporal evolution of the snowpack water equivalent in southern Québec (Canada) is proposed and implemented on a 0.1° grid. The technique combines the output of the snowpack model included in the HYDROTEL hydrological model, forced by observed temperatures and precipitations, with observed snow survey data. A strategy based on observed snow density, snowpack water equivalent and streamflow is used for model calibration. A comparison of various calibration strategies showed that the same model parameters can be used for the whole of southern Québec. It was also shown that, for operational purposes, it is sufficient to rely solely on automatic stations and to use 3 h time steps. Because snow surveys are made in deciduous forests, model parameters were adjusted to account for open areas and coniferous trees by comparing observed and simulated streamflow, using all components of the hydrological model. An assimilation technique which updates simulated water equivalent and snow density at grid points from the available snow survey data completes the operational system. An example of spring streamflow simulated using the proposed snow analysis illustrates the usefulness of the technique.

scholarly journals Reducing the uncertainty on chilling requirements for endodormancy breaking of temperate fruits by data-based parameter estimation of the dynamic model: a test case in apricot

2020 ◽  
Author(s):  
Jose A Egea ◽  
José Egea ◽  
David Ruiz
Keyword(s):  
Dynamic Model ◽  
Model Calibration ◽  
Fruit Trees ◽  
Optimal Choice ◽  
Model Parameters ◽  
Test Case ◽  
Phenological Data ◽  
Chilling Requirements ◽  
Biochemical Level ◽  
Parameter Values

Abstract The Dynamic model has been described as one of the most accurate models to quantify chill accumulation based on hourly temperatures in nuts and temperate fruits. This model considers that a dynamic process occurs at a biochemical level that determines the endodormancy breaking through the accumulation of the so-called portions. The kinetic parameters present in the model should reflect how the fruit trees integrate chilling exposure and thus they should be characteristic for each species. However, the original parameter values, reported in the late 1980s, are still being used. Even if the use of such parameter values is useful to compare among chilling requirements (CRs) for different species or cultivars, it is not the optimal choice when one intends to explain the CR variations in different years for a given cultivar. In this work we propose a data-based model calibration that makes use of phenological data for different apricot cultivars within different years to obtain model parameters, which minimize the variations among years and that have, at the same time, physical meaning to characterize the incumbent species. Results reveal that the estimation not only reduces the accumulated portion dispersion within the considered time periods but also allows to improve the CR predictions for subsequent years. We propose a set of model parameter values to predict endodormancy breaking dates in the apricot cultivars studied here.

Uncertainty analysis of calibrated parameter values of an urban storm water quality model using metropolis monte carlo algorithm

1997 ◽  
Vol 36 (5) ◽  
pp. 141-148 ◽  
Author(s):  
A. Mailhot ◽  
É. Gaume ◽  
J.-P. Villeneuve
Keyword(s):  
Monte Carlo ◽  
Uncertainty Analysis ◽  
Model Calibration ◽  
Monte Carlo Algorithm ◽  
Storm Water ◽  
Model Parameters ◽  
Calibration Data ◽  
Parameter Uncertainties ◽  
Metropolis Monte Carlo ◽  
Parameter Values

The Storm Water Management Model's quality module is calibrated for a section of Québec City's sewer system using data collected during five rain events. It is shown that even for this simple model, calibration can fail: similarly a good fit between recorded data and simulation results can be obtained with quite different sets of model parameters, leading to great uncertainty on calibrated parameter values. In order to further investigate the lack of data and data uncertainty impacts on calibration, we used a new methodology based on the Metropolis Monte Carlo algorithm. This analysis shows that for a large amount of calibration data generated by the model itself, small data uncertainties are necessary to significantly decrease calibrated parameter uncertainties. This also confirms the usefulness of the Metropolis algorithm as a tool for uncertainty analysis in the context of model calibration.

scholarly journals Application of Conceptual Rainfall-Runoff Model METQ for Simulation of Daily Runoff and Water Level: The case of the Lake Burtnieks Watershed

2008 ◽  
Vol 62 (1-2) ◽  
pp. 47-54
Author(s):  
Elga Apsīte ◽  
Ansis Zīverts ◽  
Anda Bakute
Keyword(s):  
Water Level ◽  
Correlation Coefficient ◽  
Model Calibration ◽  
Performance Model ◽  
Model Structure ◽  
Rainfall Runoff ◽  
Rainfall Runoff Model ◽  
Parameter Values ◽  
Runoff Model ◽  
Gauging Station

Application of Conceptual Rainfall-Runoff Model METQ for Simulation of Daily Runoff and Water Level: The case of the Lake Burtnieks Watershed In this study a conceptual rainfall-runoff METQ model—the latest version METQ2007BDOPT—was applied to simulate the daily runoff and water level of the Lake Burtnieks watershed from 1990 to 1999. The model structure and parameters were basically the same as in the METQ98, with some additional improvements and semi-automatical calibration performance. Model calibration was done for four rivers and one lake gauging station. The results of calibration showed a good correlation between the measured and simulated daily discharges. The Nash-Sutcliffe efficiency R2 varied from 0.90 to 0.58 and correlation coefficient r from 0.95 to 0.83. The highest values of R2 = 0.90 and r = 0.95 were obtained for the River Salaca and the lowest R2 = 0.53 and r = 0.83 for Lake Burtnieks. We observed some relationships between the model parameter values and physiographic characteristic of the sub-catchments.

scholarly journals BioModels Parameters: a treasure trove of parameter values from published systems biology models

2020 ◽  
Vol 36 (17) ◽  
pp. 4649-4654
Author(s):  
Mihai Glont ◽  
Chinmay Arankalle ◽  
Krishna Tiwari ◽  
Tung V N Nguyen ◽  
Henning Hermjakob ◽  
...  
Keyword(s):  
Systems Biology ◽  
Model Fitting ◽  
Language Models ◽  
Supplementary Information ◽  
Rate Equations ◽  
Model Parameters ◽  
Systems Biology Markup Language ◽  
Estimation Of Model Parameters ◽  
Parameter Ranges ◽  
Parameter Values

Abstract Motivation One of the major bottlenecks in building systems biology models is identification and estimation of model parameters for model calibration. Searching for model parameters from published literature and models is an essential, yet laborious task. Results We have developed a new service, BioModels Parameters, to facilitate search and retrieval of parameter values from the Systems Biology Markup Language models stored in BioModels. Modellers can now directly search for a model entity (e.g. a protein or drug) to retrieve the rate equations describing it; the associated parameter values (e.g. degradation rate, production rate, Kcat, Michaelis–Menten constant, etc.) and the initial concentrations. Currently, BioModels Parameters contains entries from over 84,000 reactions and 60 different taxa with cross-references. The retrieved rate equations and parameters can be used for scanning parameter ranges, model fitting and model extension. Thus, BioModels Parameters will be a valuable service for systems biology modellers. Availability and implementation The data are accessible via web interface and API. BioModels Parameters is free to use and is publicly available at https://www.ebi.ac.uk/biomodels/parameterSearch. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals A stochastic vision-based model inspired by zebrafish collective behaviour in heterogeneous environments

2016 ◽  
Vol 3 (1) ◽  
pp. 150473 ◽  
Author(s):  
Bertrand Collignon ◽  
Axel Séguret ◽  
José Halloy
Keyword(s):  
Experimental Data ◽  
Stochastic Process ◽  
Distribution Function ◽  
Probability Distribution Function ◽  
Collective Motion ◽  
Three Dimensional ◽  
Sensory System ◽  
Heterogeneous Environments ◽  
Parameter Values ◽  
Made In

Collective motion is one of the most ubiquitous behaviours displayed by social organisms and has led to the development of numerous models. Recent advances in the understanding of sensory system and information processing by animals impels one to revise classical assumptions made in decisional algorithms. In this context, we present a model describing the three-dimensional visual sensory system of fish that adjust their trajectory according to their perception field. Furthermore, we introduce a stochastic process based on a probability distribution function to move in targeted directions rather than on a summation of influential vectors as is classically assumed by most models. In parallel, we present experimental results of zebrafish (alone or in group of 10) swimming in both homogeneous and heterogeneous environments. We use these experimental data to set the parameter values of our model and show that this perception-based approach can simulate the collective motion of species showing cohesive behaviour in heterogeneous environments. Finally, we discuss the advances of this multilayer model and its possible outcomes in biological, physical and robotic sciences.

scholarly journals Damage Detection of Steel-Concrete Composite Beam

2018 ◽  
Vol 28 (3) ◽  
pp. 30-49
Author(s):  
Maciej Szumigała ◽  
Agnieszka Pełka-Sawenko ◽  
Tomasz Wróblewski ◽  
Małgorzata Abramowicz
Keyword(s):  
Experimental Data ◽  
Damage Detection ◽  
Discrete Model ◽  
Composite Beams ◽  
Model Parameters ◽  
Discrete Wavelet ◽  
Identification Procedure ◽  
Original Algorithm ◽  
Automated Optimization ◽  
Made In

Abstract The paper presents analysis results of steel-concrete composite beams, identification and attempts to detect damage introduced in a discrete model. Analysis of damage detection was conducted using DDL (Damage, Detection, Localization), our own original algorithm. Changes of dynamic and static parameters of the model were analysed in damage detection. Discrete wavelet transform was used for damage localization in the model. Prior to ultimate analysis, two-tier identification of discrete model parameters based on experimental data was made. In identification procedure, computational software (Python, Abaqus, Matlab) was connected in automated optimization loops. Results positively verified the original DDL algorithm for damage detection in steel-concrete composite beams, which enables further analysis using experimental data.

scholarly journals Forecasting the Bladder Tumor Size and Immune Response of a Patient Over the Time Using a Dynamic Mathematical Model

2018 ◽  
Author(s):  
Clara Burgos ◽  
Noemí García-Medina ◽  
David Martínez-Rodríguez ◽  
José-Luis Pontones ◽  
David Ramos ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Immune Response ◽  
Tumor Size ◽  
Model Calibration ◽  
Bladder Tumor ◽  
Tumor Evolution ◽  
Model Parameters ◽  
Single Patient ◽  
Dynamic Mathematical Model ◽  
Parameter Values

Bladder cancer is one of the most common malignant diseases in the urinary system and a highly aggressive neoplasm. The prognosis is not favourable usually and its evolution for particular patients is very difficult to find out. In this paper we propose a dynamic mathematical model that describes the bladder tumor growth and the immune response evolution. This model is customized for a single patient, determining appropriate model parameter values via model calibration. Due to the uncertainty of the tumor evolution, using the calibrated model parameters, we predict the tumor size and the immune response evolution over the next few months assuming three different scenarios: favourable, neutral and unfavourable. In the former, the cancer disappears; in the second a 5mm tumor is expected around the middle of August 2018; in the worst scenario, a 5mm tumor is expected around the end of May 2018. The patient has been cited around June 15th, 2018, to check the tumor size, if it exists.

scholarly journals A NEW FOUR-PARAMETER WEIBULL DISTRIBUTION WITH APPLICATION TO FAILURE TIME DATA

2020 ◽  
Vol 4 (3) ◽  
pp. 563-575
Author(s):  
Aminu Suleiman Mohammed ◽  
Fidelis Ifeanyi Ugwuowo
Keyword(s):  
Maximum Likelihood ◽  
Weibull Distribution ◽  
Failure Time ◽  
Real Life ◽  
Model Parameters ◽  
Time Data ◽  
Lifetime Model ◽  
Estimation Of Model Parameters ◽  
Parameter Values ◽  
Maximum Likelihood Technique

A lifetime model called Transmuted Exponential-Weibull Distribution was proposed in this research. Several statistical properties were derived and presented in an explicit form. Maximum likelihood technique is employed for the estimation of model parameters, and a simulation study was performed to examine the behavior of various estimates under different sample sizes and initial parameter values. Through using real-life datasets, it was empirically shown that the new model provides sufficient fits relative to other existing models.

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